Marine Analytics using Computer Vision

Project

Illustration of one of the project goals: to automatically detect and classify marine organisms in the wild.

There is a need for methods that can automate the analysis of data from underwater imaging sensors used for health monitoring of our oceans. This includes object detection, tracking, and analysis of marine organisms in various habitats. Currently, there exists only a fraction of public available datasets of underwater scenes and the amount of research within the marine vision field is limited. The goal of this project is to develop methods for automated behavioral analysis of marine organisms in the wild. The road towards this goal involves development of methods for automated behavioral analysis of fish in controlled environments, anomaly detection in the wild, and classification and tracking of marine organisms in the wild.

Scientific Work

3D-ZeF: A 3D Zebrafish Tracking Benchmark Dataset
Pedersen, M.Haurum, J. B.Bengtson, S. H. & Moeslund, T. B., 5 aug. 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR): IEEE, s. 2426-2436 11 s. (I E E E Conference on Computer Vision and Pattern Recognition. Proceedings).

Detection of Marine Animals in a New Underwater Dataset with Varying Visibility
Pedersen, M.Haurum, J. B.Gade, R.Moeslund, T. B. & Madsen, N., jun. 2019, IEEE Conference on Computer Vision and Pattern Recognition Workshops.IEEE, 10 s. (IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)).

Camera Calibration for Underwater 3D Reconstruction Based on Ray Tracing using Snell’s Law
Pedersen, M.Bengtson, S. H.Gade, R.Madsen, N. & Moeslund, T. B., 13 dec. 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).IEEE, s. 1410-1417 8 s. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops).

Essays

No Machine Learning Without Data: Critical Factors to Consider when Collecting Video Data in Marine Environments
Pedersen, M.Madsen, N. & Moeslund, T. B., okt. 2021, I: The Journal of Ocean Technology. 16, 3, s. 21-30 10 s.

Fishing with C-TUCs (Cheap Tiny Underwater Cameras) in a sea of possibilities
Madsen, N.Pedersen, M., Jensen, K. T., Møller, P. R., Andersen, R. E. & Moeslund, T. B., 2021, I: The Journal of Ocean Technology. 16, 2, s. 19-30 12 s.

Funding

Marine Analytics using Computer Vision is funded by Danmarks Frie Forskningsfond under the case number: 9131-00128B

Contact

PhD-Student: Malte Pedersen
Email: mape@create.aau.dk

Supervisor: Thomas B. Moeslund
Email: tbm@create.aau.dk